Development of the simulation platform between EAST plasma control system and the tokamak simulation code based on Simulink

Plasma control system（PCS）,mainly developed for real-time feedback control calculation,plays a significant part during normal discharges in a magnetic fusion device,while the tokamak simulation code（TSC） is a nonlinear numerical model that studies the time evolution of an axisymmetric magnetized tokamak plasma.The motivation to combine these two codes for an integrated simulation is specified by the facts that the control system module in TSC is relatively simple compared to PCS,and meanwhile,newly-implemented control algorithms in PCS,before applied to experimental validations,require numerical validations against a tokamak plasma simulator that TSC can act as.In this paper,details of establishment of the integrated simulation framework between the EAST PCS and TSC are generically presented,and the poloidal power supply model and data acquisition model that have been implemented in this framework are described as well.In addition,the correctness of data interactions among the EAST PCS,Simulink and TSC is clearly confirmed during an interface test,and in a simulation test,the RZIP control scheme in the EAST PCS is numerically validated using this simulation platform.

Prediction of multifaceted asymmetric radiation from the edge movement in density-limit disruptive plasmas on Experimental Advanced Superconducting Tokamak using random forest

Multifaceted asymmetric radiation from the edge(MARFE) movement which can cause density limit disruption is often encountered during high density operation on many tokamaks. Therefore, identifying and predicting MARFE movement is meaningful to mitigate or avoid density limit disruption for the steady-state high-density plasma operation. A machine learning method named random forest(RF) has been used to predict the MARFE movement based on the density ramp-up experiment in the 2022’s first campaign of Experimental Advanced Superconducting Tokamak(EAST). The RF model shows that besides Greenwald fraction which is the ratio of plasma density and Greenwald density limit, dβp/dt,H98and d Wmhd/dt are relatively important parameters for MARFE-movement prediction. Applying the RF model on test discharges, the test results show that the successful alarm rate for MARFE movement causing density limit disruption reaches ~ 85% with a minimum alarm time of ~ 40 ms and mean alarm time of ~ 700 ms. At the same time, the false alarm rate for non-disruptive and non-density-limit disruptive discharges can be kept below 5%. These results provide a reference to the prediction of MARFE movement in high density plasmas, which can help the avoidance or mitigation of density limit disruption in future fusion reactors.